24 citations · 92 across the 36 of their papers we have counts for
37 papers
FineBench: Benchmarking and Enhancing Vision-Language Models for Fine-grained Human Activity Understanding
Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh +2
Vision-Language Models (VLMs) have demonstrated remarkable capabilities in general video understanding, yet they often struggle with the fine-grained comprehension crucial for real…
SPATIOROUTE: Dynamic Prompt Routing for Zero-Shot Spatial Reasoning
Pawat Chunhachatrachai, Gueter Josmy Faure, Hung-Ting Su +1
Spatial question answering over egocentric video is a challenging task that requires Vision-Language Models (VLMs) to reason about 3D object positions, scene affordances, and direc…
SceneFunRI: Reasoning the Invisible for Task-Driven Functional Object Localization
Posheng Chen, Powen Cheng, Gueter Josmy Faure +2
In real-world scenes, target objects may reside in regions that are not visible. While humans can often infer the locations of occluded objects from context and commonsense knowled…
ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints
Pei-An Chen, Yong-Ching Liang, Jia-Fong Yeh +4
Intelligent embodied agents should not simply follow instructions, as real-world environments often involve unexpected conditions and exceptions. However, existing methods usually…
VLN-NF: Feasibility-Aware Vision-and-Language Navigation with False-Premise Instructions
Hung-Ting Su, Ting-Jun Wang, Jia-Fong Yeh +2
Conventional Vision-and-Language Navigation (VLN) benchmarks assume instructions are feasible and the referenced target exists, leaving agents ill-equipped to handle false-premise…
Affordance-Guided Coarse-to-Fine Exploration for Base Placement in Open-Vocabulary Mobile Manipulation
Tzu-Jung Lin, Jia-Fong Yeh, Hung-Ting Su +3
In open-vocabulary mobile manipulation (OVMM), task success often hinges on the selection of an appropriate base placement for the robot. Existing approaches typically navigate to…
MovieCORE: COgnitive REasoning in Movies
Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh +5
This paper introduces MovieCORE, a novel video question answering (VQA) dataset designed to probe deeper cognitive understanding of movie content. Unlike existing datasets that foc…
Context-Aware Replanning with Pre-explored Semantic Map for Object Navigation
Po-Chen Ko, Hung-Ting Su, Ching-Yuan Chen +3
Pre-explored Semantic Maps, constructed through prior exploration using visual language models (VLMs), have proven effective as foundational elements for training-free robotic appl…
Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses
Hung-Ting Su, Ya-Ching Hsu, Xudong Lin +5
Large language models (LLMs) equipped with chain-of-thoughts (CoT) prompting have shown significant multi-step reasoning capabilities in factual content like mathematics, commonsen…
Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation
Tsung-Han Wu, Hung-Ting Su, Shang-Tse Chen +1
The robust self-training (RST) framework has emerged as a prominent approach for semi-supervised adversarial training. To explore the possibility of tackling more complicated tasks…
HERMES: temporal-coHERent long-forM understanding with Episodes and Semantics
Gueter Josmy Faure, Jia-Fong Yeh, Min-Hung Chen +3
Long-form video understanding presents unique challenges that extend beyond traditional short-video analysis approaches, particularly in capturing long-range dependencies, processi…
Investigating Video Reasoning Capability of Large Language Models with Tropes in Movies
Hung-Ting Su, Chun-Tong Chao, Ya-Ching Hsu +4
Large Language Models (LLMs) have demonstrated effectiveness not only in language tasks but also in video reasoning. This paper introduces a novel dataset, Tropes in Movies (TiM),…
Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approach
ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1
Traditional traffic prediction, limited by the scope of sensor data, falls short in comprehensive traffic management. Mobile networks offer a promising alternative using network ac…
Tel2Veh: Fusion of Telecom Data and Vehicle Flow to Predict Camera-Free Traffic via a Spatio-Temporal Framework
ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1
Vehicle flow, a crucial indicator for transportation, is often limited by detector coverage. With the advent of extensive mobile network coverage, we can leverage mobile user activ…
Tracking-Assisted Object Detection with Event Cameras
Ting-Kang Yen, Igor Morawski, Shusil Dangi +5
Event-based object detection has recently garnered attention in the computer vision community due to the exceptional properties of event cameras, such as high dynamic range and no…
AED: Adaptable Error Detection for Few-shot Imitation Policy
Jia-Fong Yeh, Kuo-Han Hung, Pang-Chi Lo +5
We introduce a new task called Adaptable Error Detection (AED), which aims to identify behavior errors in few-shot imitation (FSI) policies based on visual observations in novel en…
TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling
ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1
To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensiv…
Unsupervised Adversarial Detection without Extra Model: Training Loss Should Change
Chien Cheng Chyou, Hung-Ting Su, Winston H. Hsu
Adversarial robustness poses a critical challenge in the deployment of deep learning models for real-world applications. Traditional approaches to adversarial training and supervis…
Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering
Hung-Ting Su, Yulei Niu, Xudong Lin +2
Causal Video Question Answering (CVidQA) queries not only association or temporal relations but also causal relations in a video. Existing question synthesis methods pre-trained qu…
BIRD-PCC: Bi-directional Range Image-based Deep LiDAR Point Cloud Compression
Chia-Sheng Liu, Jia-Fong Yeh, Hao Hsu +3
The large amount of data collected by LiDAR sensors brings the issue of LiDAR point cloud compression (PCC). Previous works on LiDAR PCC have used range image representations and f…
Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling
Hsin-Ying Lee, Hung-Ting Su, Bing-Chen Tsai +3
While recent large-scale video-language pre-training made great progress in video question answering, the design of spatial modeling of video-language models is less fine-grained t…
Fair Robust Active Learning by Joint Inconsistency
Tsung-Han Wu, Hung-Ting Su, Shang-Tse Chen +1
Fairness and robustness play vital roles in trustworthy machine learning. Observing safety-critical needs in various annotation-expensive vision applications, we introduce a novel…
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
Kuan-Chih Huang, Tsung-Han Wu, Hung-Ting Su +1
Monocular 3D object detection is an important yet challenging task in autonomous driving. Some existing methods leverage depth information from an off-the-shelf depth estimator to…
Stage Conscious Attention Network (SCAN) : A Demonstration-Conditioned Policy for Few-Shot Imitation
Jia-Fong Yeh, Chi-Ming Chung, Hung-Ting Su +2
In few-shot imitation learning (FSIL), using behavioral cloning (BC) to solve unseen tasks with few expert demonstrations becomes a popular research direction. The following capabi…